Podcasts about Ligand

Authors Drs. Jessica Ross and Alissa Cooper share insights into their JCO PO article, "Clinical and Pathologic Landscapes of Delta-Like Ligand 3 and Seizure-Related Homolog Protein 6 Expression in Neuroendocrine Carcinomas"  Host Dr. Rafeh Naqash and Drs. Ross and Cooper discuss the landscape of Delta-like ligand 3 (DLL3) and seizure-related homolog protein 6 (SEZ6) across NECs from eight different primary sites. TRANSCRIPT Dr. Rafeh Naqash: Hello and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, podcast editor for JCO PO and an Associate Professor at the OU Health Stephenson Cancer Center. Today, I'm excited to be joined by Dr. Jessica Ross, third-year medical oncology fellow at the Memorial Sloan Kettering Cancer Center, as well as Dr. Alissa Cooper, thoracic medical oncologist at the Dana-Farber Cancer Institute and instructor in medicine at Harvard Medical School. Both are first and last authors of the JCO Precision Oncology article entitled "Clinical and Pathologic Landscapes of Delta-like Ligand 3 and Seizure-Related Homolog Protein 6 or SEZ6 Protein Expression in Neuroendocrine Carcinomas." At the time of this recording, our guest disclosures will be linked in the transcript. Jessica and Alissa, welcome to our podcast, and thank you for joining us today. Dr. Jessica Ross: Thanks very much for having us. Dr. Alissa Cooper: Thank you. Excited to be here. Dr. Rafeh Naqash: It's interesting, a couple of days before I decided to choose this article, one of my GI oncology colleagues actually asked me two questions. He said, "Rafeh, do you know how you define DLL3 positivity? And what is the status of DLL3 positivity in GI cancers, GI neuroendocrine carcinomas?" The first thing I looked up was this JCO article from Martin Wermke. You might have seen it as well, on obrixtamig, a phase 1 study, a DLL3 bi-specific T-cell engager. And they had some definitions there, and then this article came along, and I was really excited that it kind of fell right in place of trying to understand the IHC landscape of two very interesting targets. Since we have a very broad and diverse audience, especially community oncologists, trainees, and of course academic clinicians and some people who are very interested in genomics, we'll try to make things easy to understand. So my first question for you, Jessica, is: what is DLL3 and SEZ6 and why are they important in neuroendocrine carcinomas? Dr. Jessica Ross: Yeah, good question. So, DLL3, or delta-like ligand 3, is a protein that is expressed preferentially on the tumor cell surface of neuroendocrine carcinomas as opposed to normal tissue. It is a downstream target of ASCL1, and it's involved in neuroendocrine differentiation, and it's an appealing drug target because it is preferentially expressed on tumor cell surfaces. And so, it's a protein, and there are several drugs in development targeting this protein, and then Tarlatamab is an approved bi-specific T-cell engager for the treatment of extensive-stage small cell lung cancer in the second line. SEZ6, or seizure-like homolog protein 6, is a protein also expressed on neuroendocrine carcinoma cell surface. Interestingly, so it's expressed on neuronal cells, but its exact role in neuroendocrine carcinomas and oncogenesis is actually pretty poorly understood, but it was identified as an appealing drug target because, similarly to DLL3, it's preferentially expressed on the tumor cell surface. And so this has also emerged as an appealing drug target, and there are drugs in development, including antibody-drug conjugates, targeting this protein for that reason. Dr. Alissa Cooper: Over the last 10 to 15 years or so, there's been an increasing focus on precision oncology, finding specific targets that actually drive the cancer to grow, not just within lung cancer but in multiple other primary cancers. But specifically, at least speaking from a thoracic oncology perspective, the field of non-small cell lung cancer has completely exploded over the past 15 years with the discovery of driver oncogenes and then matched targeted therapies. Within the field of neuroendocrine carcinomas, including small cell lung cancer but also other high-grade neuroendocrine carcinomas, there has not been the same sort of progress in terms of identifying targets with matched therapies. And up until recently, we've sort of been treating these neuroendocrine malignancies kind of as a monolithic disease process. And so recently, there's been sort of an explosion of research across the country and multiple laboratories, multiple people converging on the same open questions about why might patients with specific tumor biologies have different kind of responses to different therapies. And so first this came from, you know, why some patients might have a good response to chemo and immunotherapy, which is the first-line approved therapy for small cell lung cancer, and we also sort of extrapolate that to other high-grade neuroendocrine carcinomas. What's the characteristic of that tumor biology? And at the same time, what are other targets that might be identifiable? Just as Jesse was saying, they're expressed on the cell surface, they're not necessarily expressed in normal tissue. Might this be a strategy to sort of move forward and create smarter therapies for our patients and therefore move really into a personalized era for treatment for each patient? And that's really driving, I think, a lot of the synthesis of this work of not only the development of multiple new therapies, but really understanding which tumor might be the best fit for which therapy. Dr. Rafeh Naqash: Thank you for that explanation, Alissa. And as you mentioned, these are emerging targets, some more further along in the process with approved drugs, especially Tarlatamab. And obviously, DLL3 was something identified several years back, but drug development does take time, and readout for clinical trials takes time. Could you, for the sake of our audience, try to talk briefly about the excitement around Tarlatamab in small cell lung cancer, especially data that has led to the FDA approval in the last year, year and a half? Dr. Alissa Cooper: Sure. Yeah, it's really been an explosion of excitement over, as you're saying, the last couple of years, and work really led by our mentor, Charlie Rudin, had identified DLL3 as an exciting target for small cell lung cancer specifically but also potentially other high-grade neuroendocrine malignancies. Tarlatamab is a DLL3-targeting bi-specific T-cell engager, which targets DLL3 on the small cell lung cancer cells as well as CD3 on T cells. And the idea is to sort of introduce the cancer to the immune system, circumventing the need for MHC class antigen presentation, which that machinery is typically not functional in small cell lung cancer, and so really allowing for an immunomodulatory response, which had not really been possible for most patients with small cell lung cancer prior to this. Tarlatamab was tested in a phase 2 registrational trial of about 100 patients and demonstrated a response rate of 40%, which was very exciting, especially compared with other standard therapies which were available for small cell lung cancer, which are typically cytotoxic therapies. But most excitingly, more than even the response rate, I think, in our minds was the durability of response. So patients whose disease did have a response to Tarlatamab could potentially have a durable response lasting a number of months or even over a year, which had previously not ever been seen in this in the relapsed/refractory setting for these patients. I think the challenge with small cell lung cancer and other high-grade neuroendocrine malignancies is that a response to therapy might be a bit easier to achieve, but it's that durability. The patient's tumors really come roaring back quite aggressively pretty quickly. And so this was sort of the most exciting prospect is that durability of response, that long potential overall survival tail of the curve really being lifted up. And then most recently at ASCO this year, Dr. Rudin presented the phase 3 randomized controlled trial which compared Tarlatamab to physician's choice of chemotherapy in a global study. And the choice of chemotherapy did vary depending on the part of the world that the patients were enrolled in, but in general, it was a really markedly positive study for response rate, for progression-free survival, and for overall survival. Really exciting results which really cemented Tarlatamab's place as the standard second-line therapy for patients with small cell lung cancer whose disease has progressed on first-line chemo-immunotherapy. So that has been very exciting. This drug was FDA approved in May of 2024, and so has been used extensively since then. I think the adoption has been pretty widespread, at least in the US, but now in this global trial that was just presented, and there was a corresponding New England Journal paper, I think really confirms that this is something we really hopefully can offer to most of our patients. And I think, as we all know, that this therapy or other therapies like it are also being tested potentially in the first-line setting. So there was data presented with Tarlatamab incorporated into the maintenance setting, which also showed exciting results, albeit in a phase 1 trial, but longer overall survival than we're used to seeing in this patient population. And we await results of the study that is incorporating Tarlatamab into the induction phase with chemotherapy as well. So all of this is extraordinarily exciting for our patients to sort of move the needle of how many patients we can keep alive, feeling functional, feeling well, for as long as possible. Dr. Rafeh Naqash: Very exciting session at ASCO. I was luckily one of the co-chairs for the session that Dr. Rudin presented it, and I remember somebody mentioning there was more progress seen in that session for small cell lung cancer than the last 30, 35 years for small cell, very exciting space and time to be in as far as small cell lung cancer. Now going to this project, Jessica, since you're the first author and Alissa's the last, I'm assuming there was a background conversation that you had with Alissa before you embarked on this project as an idea. So could you, again, for other trainees who are interested in doing research, and it's never easy to do research as a resident and a fellow when you have certain added responsibilities. Could you give us a little bit of a background on how this started and why you wanted to look at this question? Dr. Jessica Ross: Yeah, sure. So, as with many exciting research concepts, I think a lot of them are derived from the clinic. And so I think Alissa and I both see a good number of patients with small cell, large cell lung cancer, and then high-grade neuroendocrine carcinomas. And so I think this was really born out of a basic conversation of we have these drugs in development targeting these two proteins, DLL3 and SEZ6, but really what is the landscape of cancers that express these proteins and who are the patients that really might benefit from these exciting new therapies. And of course, there was some data out there, but sort of less than one would imagine in terms of, you know, neuroendocrine carcinomas can really come from anywhere in the body. And so when you're seeing a patient with small cell of the cervix, for example, like what are the chances that their cancer expresses DLL3 or expresses SEZ6? So it was really derived from this pragmatic, clinically oriented question that we had both found ourselves thinking about, and we were lucky enough at MSK, we had started systematically staining patients' tumors for DLL3, tumors that are high-grade neuroendocrine carcinomas, and then we had also more recently started staining for SEZ6 as well. And so we had this nice prospectively collected dataset with which to answer this question. Dr. Rafeh Naqash: Excellent. And Alissa, could you try to go into some of the details around which patients you chose, how many patients, what was the approach that you selected to collect the data for this project? Dr. Alissa Cooper: This is perhaps a strength but also maybe a limitation of this dataset is, as Jesse alluded to, our pathology colleagues are really the stars of this paper here because we were lucky enough at MSK that they were really forethinking. They are absolute experts in the field and really forward-thinking people in terms of what information might be needed in the future to drive treatment decision-making. And so, as Jesse had said, small cell lung cancer tumor samples reflexively are stained for DLL3 and SEZ6 at MSK if there's enough tumor tissue. The other high-grade neuroendocrine carcinomas, those stains are performed upon physician request. And so that is a bit of a mixed bag in terms of the tumor samples we were able to include in this dataset because, you know, upon physician request depends on a number of factors, but actually at MSK, a number of physicians were requesting these stains to be done on their patients with high-grade neuroendocrine cancers of of other histologies. So we looked at all tumor samples with a diagnosis of high-grade neuroendocrine carcinoma of any histology that were stained for these two stains of interest. You know, I can let Jesse talk a bit more about the methodology. She was really the driver of this project. Dr. Jessica Ross: Yeah, sure. So we had 124 tumor samples total. All of those were stained for DLL3, and then a little less than half, 53, were stained for SEZ6. As Alissa said, they were from any primary site. So about half of them were of lung origin, that was the most common primary site, but we included GI tract, head and neck, GU, GYN, even a few tumors of unknown origin. And again, that's because I think a lot of these trials are basket trials that are including different high-grade neuroendocrine carcinomas no matter the primary site. And so we really felt like it was important to be more comprehensive and inclusive in this study. And then, methodologically, we also defined positivity in terms of staining of these two proteins as anything greater than or equal to 1% staining. There's really not a defined consensus of positivity when it comes to these two novel targets and staining for these two proteins. But in the Tarlatamab trials, for some of the correlative work that's been done, they use that 1% cutoff, and we just felt like being consistent with that and also using a sort of more pragmatic yes/no cutoff would be more helpful for this analysis. Dr. Alissa Cooper: And that was a point of discussion, actually. We had contemplated multiple different schemas, actually, for how to define thresholds of positivity. And I know you brought up that question before, what does it mean to be DLL3 positive or DLL3 high? I think you were alluding to prior that there was a presentation of obrixtamig looking at extra-pulmonary neuroendocrine carcinomas, and they actually divvied up the results between DLL3 50% or greater versus DLL3 low under 50%. And they actually did demonstrate differential efficacy certainly, but also some differential safety as well, which is very provocative and that kind of analysis has not been presented for other novel therapies as far as I'm aware. I could be wrong, but as far as I'm aware, that was sort of the first time that we saw a systematic presentation of considering patients to be, quote unquote, "high" or "low" in these sort of novel targets. I think it is important because the label for Tarlatamab does not require any DLL3 expression at all, actually. So it's not hinging upon DLL3 expression. They depend on the fact that the vast majority of small cell lung cancer tumors do express DLL3, 85% to 90% is what's been demonstrated in a few studies. And so, there's not prerequisite testing needed in that regard, but maybe for these extra-pulmonary, other histology neuroendocrine carcinomas, maybe it does matter to some degree. Dr. Rafeh Naqash: Definitely agree that this evolving landscape of trying to understand whether an expression for something actually really does correlate with, whether it's an immune cell engager or an antibody-drug conjugate is a very evolving and dynamically moving space. And one of the questions that I was discussing with one of my friends was whether IHC positivity and the level of IHC positivity, as you've shown in one of those plots where you have double positive here on the right upper corner, you have the double negative towards the left lower, whether that somehow determines mRNA expression for DLL3. Obviously, that was not the question here that you were looking at, but it does kind of bring into question certain other aspects of correlations, expression versus IHC. Now going to the figures in this manuscript, very nicely done figures, very easy to understand because I've done the podcast for quite a bit now, and usually what I try to do first is go through the figures before I read the text, and and a lot of times it's hard to understand the figures without reading the text, but in your case, specifically the figures were very, very well done. Could you give us an overview, a quick overview of some of the important results, Jessica, as far as what you've highlighted in the manuscript? Dr. Jessica Ross: Sure. So I think the key takeaway is that, of the tumors in our cohort, the majority were positive for DLL3 and positive for SEZ6. So about 80% of them were positive for DLL3 and 80% were positive for SEZ6. About half of the tumors were stained for both proteins, and about 65% of those were positive as well. So I think if there's sort of one major takeaway, it's that when you're seeing a patient with a high-grade neuroendocrine carcinoma, the odds are that their tumor will express both of these proteins. And so that can sort of get your head thinking about what therapies they might be eligible for. And then we also did an analysis of some populations of interest. So for example, we know that non-neuroendocrine pathologies can transform into neuroendocrine tumors. And so we specifically looked at that subset of patients with transformed tumors, and those were also- the majority of them were positive, about three-quarters of them were positive for both of these two proteins. We looked at patients with brain met samples, again, about 70% were positive. And then I'd say the last sort of population of interest was we had a subset of 10 patients who had serial biopsies stained for either DLL3 or SEZ6 or both. In between the two samples, these patients were treated with chemotherapy. They were not treated with targeted therapy, but interestingly, in the majority of cases, the testing results were concordant, meaning if it was DLL3 positive to begin with, it tended to remain DLL3 positive after treatment. And so I think that's important as well as we think about, you know, a patient who maybe had DLL3 testing done before they received their induction chemo-IO, we can somewhat confidently say that they're probably still DLL3 positive after that treatment. And then finally, we did do a survival analysis among specifically the patients with lung neuroendocrine carcinomas. We looked at whether DLL3 expression affected progression-free survival on first-line platinum-etoposide, and then we looked at did it affect overall survival. And we found that it did not have an impact or the median progression-free survival was similar whether you were DLL3 positive or negative. But interestingly, with overall survival, we found that DLL3 positivity actually correlated with slightly improved overall survival. These were small numbers, and so, you know, I think we have to interpret this with caution, for sure, but it is interesting. I think there may be something to the fact that five of the patients who were DLL3 positive were treated with DLL3-targeting treatments. And so this made me think of, like in the breast cancer world, for example, if you have a patient with HER2-positive disease, it initially portended worse prognosis, more aggressive disease biology, but on the other hand, it opens the door for targeted treatments that actually now, at least with HER2-positive breast cancer, are associated with improved outcomes. And so I think that's one finding of interest as well. Dr. Rafeh Naqash: Definitely proof-of-concept findings here that you guys have in the manuscript. Alissa, if I may ask you, what is the next important step for a project like this in your mind? Dr. Alissa Cooper: Jesse has highlighted a couple of key findings that we hope to move forward with future investigative studies, not necessarily in a real-world setting, but maybe even in clinical trial settings or in collaboration with sponsors. Are these biomarkers predictive? Are they prognostic? You know, those are still- we have some nascent data, data has been brewing, but I think that we we still don't have the answers to those open questions, which I think are critically important for determining not only clinical treatment decision-making, but also our ability to understand sequencing of therapies, prioritization of therapies. I think a prospective, forward-looking project, piggybacking on that paired biopsy, you know, we had a very small subset of patients with paired biopsies, but a larger subset or cohort looking at paired biopsies where we can see is there evolution of these IHC expression, even mRNA expression, as you're saying, is there differential there? Are there selection pressures to targeted therapies? Is there upregulation or downregulation of targets in response not just to chemotherapy, but for example, for other sort of ADCs or bi-specific T-cell engagers? I think those are going to be critically important future studies which are going to be a bit challenging to do, but really important to figure out this key clinical question of sequencing, which we're all contemplating in our clinics day in and day out. If you have a patient, and these patients often can be sick quite quickly, they might have one shot of what's the next treatment that you're going to pick. We can't guarantee that every patient is going to get to see every therapy. How can you help to sort of answer the question of like what should you offer? So I think that's the key question sort of underlying any future work is how predictive or prognostic are these biomarkers? What translational or correlative studies can we do on the tissue to understand clinical treatment decision-making? I think those are the key things that will unfold in the next couple of years. Dr. Rafeh Naqash: The last question for you, Alissa, that I have is, you are fairly early in your career, and you've accomplished quite a lot. One of the most important things that comes out from this manuscript is your mentorship for somebody who is a fellow and who led this project. For other junior investigators, early-career investigators, how did you do this? How did you manage to do this, and how did you mentor Jessica on this project with some of the lessons that you learned along the way, the good and other things that would perhaps help other listeners as they try to mentor residents, trainees, which is one of the important things of what we do in our daily routine? Dr. Alissa Cooper: I appreciate you calling me accomplished. Um, I'm not sure how true that is, but I appreciate that. I didn't have to do a whole lot with this project because Jesse is an extraordinarily smart, driven, talented fellow who came up with a lot of the clinical questions and a lot of the research questions as well. And so this project was definitely a collaborative project on both of our ends. But I think what was helpful from both of our perspectives is from my perspective, I could kind of see that this was a gap in the literature that really, I think, from my work leading clinical trials and from treating patients with these kinds of cancers that I really hoped to answer. And so when I came to Jessica with this idea as sort of a project to complete, she was very eager to take it and run with it and also make it her own. You know, in terms of early mentorship, I have to admit this was the first project that I mentored, so it was a great learning experience for me as well because as an early-career clinician and researcher, you're used to having someone else looking over your shoulder to tell you, "Yes, this is a good journal target, here's what we can anticipate reviewers are going to say, here are other key collaborators we should include." Those kind of things about a project that don't always occur to you as you're sort of first starting out. And so all of that experience for me to be identifying those more upper-level management sort of questions was a really good learning experience for me. And of course, I was fantastically lucky to have a partner in Jesse, who is just a rising star. Dr. Jessica Ross: Thank you. Dr. Rafeh Naqash: Well, excellent. It sounds like the first of many other mentorship opportunities to come for you, Alissa. And Jessica, congratulations on your next step of joining and being faculty, hopefully, where you're training. Thank you again, both of you. This was very insightful. I definitely learned a lot after I reviewed the manuscript and read the manuscript. Hopefully, our listeners will feel the same. Perhaps we'll have more of your work being published in JCO PO subsequently. Dr. Alissa Cooper: Hope so. Thank you very much for the opportunity to chat today. Dr. Jessica Ross: Yes, thank you. This was great. Dr. Rafeh Naqash: Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review and be sure to subscribe so as you never miss an episode. You can find all ASCO shows at asco.org/podcasts. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement. Disclosures: Dr. Alissa Jamie Cooper Honoraria Company: MJH Life Scienes, Ideology Health, Intellisphere LLC, MedStar Health, Physician's Education Resource, LLC,  Gilead Sciences, Regeneron, Daiichi Sankyo/Astra Zeneca, Novartis,  Research Funding: Merck, Roche, Monte Rosa Therapeutics, Abbvie, Amgen, Daiichi Sankyo/Astra Zeneca Travel, Accommodations, Expenses: Gilead Sciences

In this podcast episode, MRS Bulletin's Laura Leay interviews Yaroslava Yingling and Joseph Tracy from North Carolina State University about their study on iron oxide colloidal nanoparticles (NPs) coated in oleylamine ligands. By combining experimental work with molecular simulations, their research group determined how to optimize ethanol solvent-mediated ligand stripping in order to control the functionality of the NPs. This work was published in a recent issue of Advanced Materials Interfaces.

Obesity is one of the most pressing health challenges of our time, with genetic and molecular factors playing a crucial role in how our bodies regulate weight. In this season opener, we explore the science behind obesity, focusing on how hormones, genetics, and brain circuits influence feeding behavior and body weight. Join us for a fascinating discussion about the interplay between molecular biology and real-world health outcomes.Our guest, Dr. Giles Yeo, is a professor of molecular neuroendocrinology at the University of Cambridge and an expert in the genetics of obesity. With decades of research experience, Dr. Yeo dives into how hormones like GLP-1 interact with the brain and how genetic mutations can affect eating behaviors. He also explains the innovative molecular biology techniques his lab uses to map brain circuits and decode the genetic influences on body weight.But this episode isn't all about the lab. Dr. Yeo shares his journey from studying the genetics of Japanese pufferfish to becoming a leading voice in obesity research and science communication. Whether he's decoding how Ozempic works or reflecting on the importance of good science communication, Dr. Yeo's passion for the field—and his knack for making complex topics relatable—shines through. Subscribe to get future episodes as they drop and if you like what you're hearing we hope you'll share a review or recommend the series to a colleague.  Visit the Invitrogen School of Molecular Biology to access helpful molecular biology resources and educational content, and please share this resource with anyone you know working in molecular biology. For Research Use Only. Not for use in diagnostic procedures.

Some debate that synthetic organic chemistry strategies have become stale, but Dr. Todd Hyster of Princeton University's Hyster Lab disagrees.Todd fell in love with organic chemistry early in his education, but it wasn't until he got turned on to enzyme catalysis that he found his true calling. He's built a career using engineered enzymes to facilitate chemical transformations that would otherwise not be possible. Specifically, he and his team focus on photo-enzymatic catalysis where they use a combination of light and engineered proteins to drive new chemical transformations.Join us to learn about his work, the methods involved, and the types of transformations being accomplished, which is beyond enantioselective synthesis, by the way. This stimulating conversation delves into the tactical and philosophical aspects of the synthetic chemistry, enzyme catalysis, and even the realities of academic funding and industry collaboration. Related episodes: Season 3, Ep.2: Making impossible moleculesSeason 2, Ep.3: Rethinking catalysisBonus content!Access bonus content curated by this episode's guest by visiting www.thermofisher.com/chemistry-podcast for links to recent publications, podcasts, books, videos and more.View the video of this episode on www.thermofisher.com/chemistry-podcast.A free thank you gift for our listeners! Request your free Bringing Chemistry to Life t-shirt on our episode website.Use code BCTLisn3R in September, and cHeMcas+ng in October We read every email so please share your questions and feedback with us! Email helloBCTL@thermofisher.com

Did you know that targeting the OX40-OX40 ligand (OX40-OX40L) pathway may lead to long-term remission in atopic dermatitis (AD)? Credit available for this activity expires: 6/26/25 Earn Credit / Learning Objectives & Disclosures: https://www.medscape.org/viewarticle/1001214?ecd=bdc_podcast_libsyn_mscpedu

In this groundbreaking episode of the Cognitive Revolution, we explore the intersection of AI and biology with expert Amelie Schreiber. Learn about the advances in drug design, protein network engineering, and the unfolding AI revolution in scientific discovery. Discover the implications for human health, longevity, and the future of biological research. Join us as we delve into an exciting conversation that may redefine our understanding of biology and medicine. SPONSORS: Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds; offers one consistent price, and nobody does data better than Oracle. If you want to do more and spend less, take a free test drive of OCI at https://oracle.com/cognitive The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://bit.ly/BraveTCR Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention “Turpentine” to skip the waitlist. Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off https://www.omneky.com/ CHAPTERS: (00:00:00) Introduction (00:04:53) Introduction to Amelie Schreiber and the Podcast (00:08:59) Understanding Protein Interactions (00:11:45) Traditional Methods vs. AI Approaches (00:13:51) Molecular Dynamics and AI Models (00:18:02) AlphaFold and Protein Structure Prediction (00:18:43) Sponsors: Oracle | Brave (00:20:51) Protein Dynamics and New AI Models (00:32:36) Sponsors: Squad | Omneky (00:34:22) Challenges in Protein Interaction Models (00:44:44) Generalization and Data Splitting in AI Models (00:48:43) Advanced AI Models for Protein Complexes (00:52:25) Practical Applications of AI in Biochemistry (01:01:53) Designing Protein Sequences with Ligand and PNN (01:05:19) Binder Design and Fold Conditioning (01:08:48) Challenges and Bottlenecks in Drug Discovery (01:16:09) Adoption and Accessibility of New Technologies (01:21:04) Future Prospects and Ethical Considerations (01:37:08) The Role of AI Agents in Biological Research (01:40:18) Balancing Innovation and Safety in Biotechnology

Most of us don't grow up across the street from a chemistry building or know from an early age that we want to be a scientist, but Alan Dyke, VP of Business Development for ProChem, Inc. (CTO of Boulder Scientific Company at the time of the interview) did and became a chemist. Dr. Alan Dyke, former colleague, and friend of Paolo's, shares his career path and discusses the history and current state of the field of catalysis. With a father that taught university-level chemistry, and a brother in the field, it may not be surprising that Alan Dyke became a chemist, but it is surprising is that he's considered to be the outcast of the family for choosing a commercial career instead of taking an academic route. But, as he'll passionately reveal, there are upsides to choosing a non-academic career. Join us for a wonderful conversation where Paolo and Alan recount their shared history and the evolution of the catalysis field over recent decades. They discuss the evolution of homogeneous cross-coupling, biocatalysis, metathesis, and metallocene chemistry. Application of catalysis to fields as varied as pharmaceuticals and polymers is discussed, along with sustainability and other trends and dynamics in the field. Overcome your activation energy and join us!Related episodes: Season 1, Ep.2: Reinventing plastics, one reaction at a time Season 2, Ep.1: Chemistry: a modern American dreamSeason 2, Ep.6: The charm of the forgotten elements Bonus content!Access bonus content curated by this episode's guest by visiting www.thermofisher.com/chemistry-podcast for links to recent publications, podcasts, books, videos and more.View the video of this episode on www.thermofisher.com/chemistry-podcast. A free thank you gift for our listeners! Visit the episode website and request your free Bringing Chemistry to Life t-shirt.Use Podcast Code:  laBcheM in March or sc13nc3 in April We read every email so please share your questions and feedback with us! Email helloBCTL@thermofisher.com About Your HostPaolo Braiuca grew up in the North-East of Italy and holds a PhD in Pharmaceutical Sciences from nearby esteemed University of Trieste, Italy. He developed expertise in biocatalysis during his years of post-doctoral research in Italy and the UK, where he co-founded a startup company. With this new venture, Paolo's career shifted from R&D to business development, taking on roles in commercial, product management, and marketing. He has worked in the specialty chemicals, biotechnology, and pharmaceutical markets in Germany and the UK, where he presently resides. He is currently the Director of Global Market Development in the Laboratory Chemicals Division at Thermo Fisher Scientific™ which put him in the host chair of the Bringing Chemistry to Life podcast. A busy father of four, in what little free time he has, you'll find him inventing electronic devices with the help of his loyal 3D-printer and soldering iron. And if you ask him, he'll call himself a “maker” at heart.

Dana Rathkopf describes phase 1 data for the androgen receptor ligand-directed degrader in prostate cancer

References British J of Pharmacology 2015. Volume172, Issue17 September Pages 4319-4330 Chem Rev. 2011 Oct 12; 111(10): 6321–6340 JBiol Chem. 2020 Jul 17; 295(29): 10045–10061 Mozart, WA. 1768. January. Symphony #7 in D major K.45.composed in Vienna just 10 days before he turned 12 years old. https://youtu.be/ABOle_eSq9c?si=GcA8EvXbpEZP0W0A --- Send in a voice message: https://podcasters.spotify.com/pod/show/dr-daniel-j-guerra/message Support this podcast: https://podcasters.spotify.com/pod/show/dr-daniel-j-guerra/support

Tom Pesnot is the Head of Medicinal Chemistry at Concept Life Sciences. I invited him to talk about AI and virtual screening in the drug discovery process.By way of review, Tom laid out the overall process of discovery. One needs to identify a target whose activity can be modulated in a way that is of course, relevant to the disease of interest. Most often we are trying to stop a protein from carrying out its normal function. Then we are looking for hits — interactions of candidate compounds with the target molecule. The quality of those hits are important. Typically, this has been done in high throughput screening using in vitro assays. This requires lots of compounds and lots of assays, making the process inaccessible for many. As you might imagine, it is very expensive with fancy robots etc.All of this provides the rationale for virtual screening because computers are becoming more powerful for predicting interactions between small molecule compounds and target proteins.Instead of starting with a compound collection (that few have access to), you start with a database. It's possible to virtually make tens of billions of compounds in silico for screening. What blew my mind was the fact that they are only screening molecules that can be made in two or three steps from existing building blocks. Tens of billions! That means the time from identification to testing is essentially the time needed for shipping the constituent compounds.And of course, at the other end, you still need a model to recapitulate the proposed activity in vitro.AI is used along with known protein structures to see what molecules fit and how well in the target's binding site. I asked about binding in other places that would affect activity. Ligand-based interactions are legitimate, Tom told me. For example, GPCRs (G-protein coupled receptors) elicit different pharmacology depending on where binding occurs, but AI has more impact in structure-based screening focused on active site binding.Thanks for reading cc: Life Science! Subscribe for free to receive new posts and support my work.Either way, I appreciate you spending time here.The big innovation is narrowing down the possibilities to test. The traditional brute force approach, even with AI, is to screen one compound at a time. This requires huge amounts of computing power. An AI-derived algorithm that tests the most likely candidates can accelerate the process 1000-fold.“And that means that because you're accelerating the process by a hundredfold or a thousandfold, then you don't need 10,000 CPUs. But you need 12 CPUs. And then you can screen billions of compounds using, you know, average Joe's (gaming) computer and get that done in a week. So that's really one of the aspects where AI is having a huge impact on virtual screening. It means that even for huge collections, this process is accessible to small biotechs, to everybody.”While machine learning is working on making hits more relevant, false positives are a still a challenge. Many things need to work well for a drug to be approved. Safety, efficacy, solubility etc are all important.We're not making virtual medicinesSo how many compounds from a screening will be tested in an actual in vitro assay? Tom says they might start with 500-1000 molecules. Then those are whittled down to 50-100.Then they make/buy them and do an in vitro assay.I've been curious about where we are in terms of AI developed drugs in the pipeline. It's still early days with respect to approved drugs from discovery by AI. According to this article, as of August 2023, none are yet at the approval stage.One big problem, yet to be overcome, is that typically negative data are not published.“The problem is, We have a lot of positive data points, negative data points are not necessarily as available because we don't tend to publish negative data. Even though there are some channels to do that and the problem is to build and test and validate a machine learning model or any model, you need to have positive and negative data.”There are many reasons why a tested compound doesn't work including a specific protocol or human error. Yet, I can't help but wonder how much money and effort is wasted on testing compounds that have already been shown to be ineffective, but the data not shared.Worse yet is the fact that there are published papers with fake data written by AI which is a whole other topic.Maybe drug discovery is getting harder because we are getting to the proteins that are involved in more complex processes. But Tom points out that many targets that were thought to be undruggable have seen success. Ideally, AI will help us get there faster.My question for all of you: Where else might AI be applied to make drug discovery more successful, improving on the 90% failure rate? And is anyone working on that?Your deepest insights are your best branding. I'd love to help you share them. Chat with me about custom content for your life science brand. Or visit my website. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

In this week's episode we'll discuss the prognostic significance of splicing factor gene mutations in newly diagnosed AML, learn more about the findings from a multi-omics study of therapy resistance in multiple myeloma, and discuss the effects of KIT ligand deletion on systemic KIT levels and hematopoietic stem cell homeostasis. 

References Nature Immunology 2022. volume 23, pages 1208–1221 Signal Transduction and Targeted Therapy 2021. volume 6, Article number: 412. --- Send in a voice message: https://podcasters.spotify.com/pod/show/dr-daniel-j-guerra/message

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.07.05.547814v1?rss=1 Authors: Bedolla, A. M., Wegman, E., Weed, M., Paranjpe, A., Alkhimovitch, A., Ifergan, I., McClain, L., Luo, Y. Abstract: While TGF-{beta} signaling is essential for microglial function, the cellular source of TGF-{beta} ligand and its spatial regulation remains unclear in the adult CNS. Our data support that microglia, not astrocytes or neurons, are the primary producers of TGF-{beta}1 ligands needed for microglial homeostasis. Microglia (MG)-Tgfb1 inducible knockout (iKO) leads to the activation of microglia featuring a dyshomeostatic transcriptomic profile that resembles disease-associated microglia (DAMs), injury-associated microglia, and aged microglia, suggesting that microglial self-produced TGF-{beta}1 ligands are important in the adult CNS. Interestingly, astrocytes in MG-Tgfb1 iKO mice show a transcriptome profile that closely aligns with A1-like astrocytes. Additionally, using sparse mosaic single-cell microglia iKO of TGF-{beta}1 ligand, we established an autocrine mechanism for TGF-{beta} signaling. Importantly MG-Tgfb1 iKO mice show cognitive deficits, supporting that precise spatial regulation of TGF-{beta}1 ligand derived from microglia is critical for the maintenance of brain homeostasis and normal cognitive function in the adult brain. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

In this week's episode we'll discuss the findings from a study exploring the combination of concurrent pembrolizumab, adriamycin, vinblastine, and dacarbazine in newly diagnosed classical Hodgkin lymphoma, learn more about the effects of targeting the CD40/CD40-ligand axis in Waldenström Macroglobulinemia, and review the findings from a study aimed at improving the bone marrow homing of CAR-cytokine induced killer cells in AML.

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.03.28.534513v1?rss=1 Authors: pan, x., ye, f., Ning, P., Zhang, Z., Zhang, B., Chen, G., Gao, W., Qiu, C., Wu, Z., Gong, K., Li, J., Xia, J., Du, Y. Abstract: Hydroxycarboxylic acid receptor 2 (HCAR2) belongs to the family of class A G-protein-coupled receptors with key roles in regulating lipolysis and free fatty acid formation in humans. It is deeply involved in many pathophysiological processes and serves as an attractive target for the treatment of neoplastic, autoimmune, neurodegenerative, inflammatory, and metabolic diseases. Here, we report four cryo-EM structures of human HCAR2-Gi1 complexes with or without agonists, including the drugs niacin and acipimox, and the highly subtype-specific agonist MK-6892. Combined with molecular docking and functional analysis, we have revealed the recognition mechanism of HCAR2 for different agonists and summarized the general pharmacophore features of HCAR2 agonists, which are based on three key residues R1113.36, S17945.52, and Y2847.43. Notably, the MK-6892-HCAR2 structure shows an extended binding pocket relative to other agonist-bound HCAR2 complexes. In addition, the key residues that determine the ligand selectivity between the HCAR2 and HCAR3 are also illuminated. Our findings provide structural insights into the ligand recognition, selectivity, activation, and G protein coupling mechanism of HCAR2, which sheds light on the design of new HCAR2-targeting drugs for greater efficacy, higher selectivity, and fewer or no side effects. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.03.03.530963v1?rss=1 Authors: Van Renterghem, C., Nemecz, A., Delarue-Cochin, S., Joseph, D., Corringer, P.-J. Abstract: Using a bacterial orthologue of brain pentameric neurotransmitter receptors, we show that the orthotopic/orthosteric agonist site and the adjacent vestibular region are functionally inter-dependent in mediating compound-elicited modulation. We propose that the two sites in the extracellular domain are involved ''in series'', a mechanism which may have relevance to Eukaryote receptors. We show that short-chain di-carboxylate compounds are positive modulators of GLIC. The most potent compound identified is fumarate, known to occupy the orthotopic/orthosteric site in previously published crystal structures. We show that intracellular pH modulates GLIC allosteric transitions, as previously known for extracellular pH. We report a caesium to sodium permeability ratio (PCs/PNa) of 0.54 for GLIC ion pore. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2023.02.13.528256v1?rss=1 Authors: MAITI, S., Das, S. Abstract: Formins are a group of actin-binding proteins that mediate nascent actin filament polymerization, filament elongation, and barbed end capping function, thereby regulating different cellular and developmental processes. Developmental processes like vertebrate gastrulation, neural growth cone dynamics, and limb development require formins to function in a regulated manner. Formin binding proteins like Rho GTPase regulates activation of auto-inhibited conformation of diaphanous formins. Unlike other diaphanous formins, Formin1 (FMN1), a non-diaphanous formin, is not regulated by Rho GTPase. FMN1 acts as an antagonist of the BMP signaling pathway during limb development. Several previous reports demonstrated that WW domain-containing proteins can interact with poly-proline-rich amino acid stretches of formins and play a crucial role in developmental processes. WW domain-containing FNBP4 protein plays an essential role in limb development. It has been hypothesized that the interaction between FNBP4 and FMN1 can further attribute to the role in limb development through the BMP signaling pathway. In this study, we have elucidated the binding kinetics of FNBP4 and FMN1 using surface plasmon resonance and enzyme-linked immunosorbent assays. Our findings confirm that the FNBP4 exhibits interaction with the poly-proline-rich formin homology 1 (FH1) domain of FMN1. Furthermore, only the first WW1 domains is involved in the interaction between the two domains. Thus, this study sheds light on the binding potentialities of WW domains of FNBP4 and their possible contribution to the regulation of FMN1 function. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2022.12.15.520545v1?rss=1 Authors: Shi, Y., Ghetti, B., Goedert, M., Scheres, S. Abstract: Positron emission tomography (PET) imaging allows monitoring the progression of amyloid aggregation in the living brain. [18F]-Flortaucipir is the only approved PET tracer compound for the visualisation of tau aggregation. Here, we describe cryo-EM experiments on tau filaments in the presence and absence of flortaucipir. We used tau filaments isolated from the brain of an individual with Alzheimer's disease (AD), and from the brain of an individual with primary age-related tauopathy (PART) with a co-pathology of chronic traumatic encephalopathy (CTE). Unexpectedly, we were unable to visualise additional cryo-EM density for flortaucipir for AD paired helical or straight filaments (PHFs or SFs), but we did observe density for flortaucipir binding to CTE Type I filaments from the case with PART. In the latter, flortaucipir binds in a 1:1 molecular stoichiometry with tau, adjacent to lysine 353 and aspartate 358. By adopting a tilted geometry with respect to the helical axis, the 4.7 A distance between neighbouring tau monomers is reconciled with the 3.5 A distance consistent with pi-pi-stacking between neighbouring molecules of flortaucipir. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

What is the Role of Artificial Intelligence in Drug Development and Drug Discovery?⭐ In this episode, we talk about:Deep Mind's AlphafoldInvesting in Life Science companiesThe State of AI in Drug Development and Drug DiscoveryHow does GDPR limit the development of AI in Drug DiscoveryThe Human Genome and AIToday's speaker is Marco Schmidt, CSO of Biotx.aiMarco had an exceptional academic career. He won the best PhD of the year award in Chemistry in his home country Germany and then went on to do a Post-Doc at the University of Cambridge.⭐ EPISODE Links:Marco Schmidt on Linkedin Youtube

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2022.10.19.512855v1?rss=1 Authors: Duan, J., Liu, H., Ji, Y., Yuan, Q., Li, X., Wu, K., Gao, T., Zhu, S., Jiang, Y., Yin, W., Xu, H. E. Abstract: Phosphorylation of G protein-coupled receptors (GPCR) by GPCR kinases (GRKs) desensitizes G protein signaling and promotes arrestin signaling, which is also modulated by biased ligands. Molecular assembly of GRKs to GPCRs and the basis of GRK-mediated biased signaling remain largely unknown due to the weak GPCR-GRK interactions. Here we report the complex structure of neurotensin receptor 1 (NTSR1) bound to GRK2, Gaq, and an arrestin-biased ligand, SBI-553, at a resolution of 2.92 Angstrom. The high-quality density map reveals the clear arrangement of the intact GRK2 with the receptor, with the N-terminal helix of GRK2 docking into the open cytoplasmic pocket formed by the outward movement of the receptor TM6, analogous of the binding of G protein to the receptor. Strikingly, the arrestin-biased ligand is found at the interface between GRK2 and NTSR1 to enhance GRK2 binding. The binding mode of the biased ligand is compatible with arrestin binding but is clashed with the binding of a G protein, thus provide an unambiguous mechanism for its arrestin-biased signaling capability. Together, our structure provides a solid model for understanding the details of GPCR-GRK interactions and biased signaling. Copy rights belong to original authors. Visit the link for more info Podcast created by Paper Player, LLC

Proteins are the functional unit of all life processes and as such it is important that we maximise our understanding of their interactions with other molecules in order to study their effects. Dr. Tomas Rube talked with us about his recently developed method for estimating protein-ligand binding affinity and the importance of this for understanding transcription factors and how they control our genes.

Welcome all to IS PHARMACOLOGY DIFFICULT Podcast! I am Dr Radhika Vijay.Essence of Friendship is in "Sincerity" and "Frankness" of thoughts and words, else it becomes senseless.Today's dialogue is all about Receptor mechanisms of drug action. Actually we are starting it! Initially I will talk about about definition of receptors, and a few more terms to comment upon and define to ge to furnish our concepts and understanding of the detailed theory of receptor action mechanism in a smooth and wonderful way. Future holds diving in depth of the subject, so its always good to get acquainted with the Vocabulary, it really helps to enrich one's knowledge!! With dialogue about receptor, agonist , antagonist, partial agonist and ligand, I will be building up the vocabulary to understand the future details nicely! Pointing to the noise of ticking clock, I will be wrapping up to avoid further confusions and strains, , Always keep in mind, "Early to rise gonna make you real wise"!!! For all the updates and latest episodes of my podcast, please visit www.ispharmacologydifficult.com where you can also sign up for a free monthly newsletter of mine. It actually contains lot of updates about the medical sciences, drug information and my podcast updates also. You can follow me on different social media handles like twitter, insta, facebook and linkedin. They all are with same name "IS PHARMACOLOGY DIFFICULT". If you are listening for the first time, do follow me here, whatever platform you are consuming this episode, stay tuned, do rate and review on ITunes, Apple podcasts, stay safe, stay happy, stay enlightened, Thank you!! You can access various links via - https://linktr.ee/ispharmacologydifficult

Learn about how to combat revenge bedtime procrastination; the power of elephant trunks; and how pineapples eat you back. How to combat "revenge bedtime procrastination" by Kelsey Donk Cohut, M. (2021, March 19). Revenge bedtime procrastination: A plight of our times? Medicalnewstoday.com; Medical News Today. https://www.medicalnewstoday.com/articles/revenge-bedtime-procrastination-a-plight-of-our-times  Patia Braithwaite. (2021, May 28). Revenge Bedtime Procrastination: 6 Ways to Manage It. SELF; SELF. https://www.self.com/story/revenge-bedtime-procrastination  Kroese, F. M., De Ridder, D. T. D., Evers, C., & Adriaanse, M. A. (2014). Bedtime procrastination: introducing a new area of procrastination. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00611  Elephants can suck water into their trunks 30 times faster than you sneeze by Cameron Duke How an elephant's trunk manipulates air to eat and drink. (2021). EurekAlert! https://www.eurekalert.org/pub_releases/2021-06/giot-hae060121.php  Schulz, A. K., Ning Wu, J., Ha, S. Y. S., Kim, G., Braccini Slade, S., Rivera, S., Reidenberg, J. S., & Hu, D. L. (2021). Suction feeding by elephants. Journal of the Royal Society Interface, 18(179), 20210215. https://doi.org/10.1098/rsif.2021.0215  Pineapples eat you back, thanks to a meat-tenderizer enzyme by Grant Currin Here's The Scientific Reason Pineapple Burns Your Mouth. (2018). NowThis News. https://nowthisnews.com/videos/food/heres-the-scientific-reason-pineapple-burns-your-mouth  Scheve, T. (2008, August 4). Why do pineapple enzymes tenderize steak -- and your tongue? HowStuffWorks. https://science.howstuffworks.com/innovation/edible-innovations/pineapple-enzyme-tenderize-steak1.htm  Di Lullo, G. A., Sweeney, S. M., Körkkö, J., Ala-Kokko, L., & San Antonio, J. D. (2002). Mapping the Ligand-binding Sites and Disease-associated Mutations on the Most Abundant Protein in the Human, Type I Collagen. Journal of Biological Chemistry, 277(6), 4223–4231. https://doi.org/10.1074/jbc.m110709200  Follow Curiosity Daily on your favorite podcast app to learn something new every day withCody Gough andAshley Hamer. Still curious? Get exclusive science shows, nature documentaries, and more real-life entertainment on discovery+! Go to https://discoveryplus.com/curiosity to start your 7-day free trial. discovery+ is currently only available for US subscribers. See omnystudio.com/listener for privacy information.

My AP Biology Thoughts  Unit 4 Cell Communication and Cell CycleWelcome to My AP Biology Thoughts podcast, my name is Pauline Brillouet and I am your host for episode #87 called Unit 4 Cell Communication and Cell Cycle: Reception: Ligand Gated Ion Channels and Intracellular Receptors. Today we will be discussing the function and examples of these two types of receptors. Segment 1: Introduction to Reception: Ligand Gated Ion Channels and Intracellular ReceptorsLigand gated ion channels and intracellular receptors are both involved in the first step of a signaling pathway known as reception. Reception is the process where a signal, or otherwise called a ligand, binds to a receptor. The ligand-binding domain of the receptor recognizes the specific chemical messenger to then start transduction. One thing to note is that the binding of ligand and receptor is noncovalent, so it is temporary and functions like an enzyme-substrate complex where size and shape of the signal is essential.  The main difference between the two receptors we are exploring is their location. Ligand-gated ion channels are membrane proteins. Meaning they are embedded in the membrane. Like the name suggests, intracellular receptors obviously lie within the cell.  Segment 2: More About Reception: Ligand Gated Ion Channels and Intracellular ReceptorsLigand gated ion channels either open or close in response to binding. They conduct ion flow. An example is a neurotransmitter binding to neurons, which opens the gate for Na+ Intracellular receptors require ligands that are small or nonpolar because they can diffuse through the membrane. An example of this is the sex hormone estrogen or any steroid hormone. When a hormone enters a cell and binds to its receptor, it causes the receptor to change shape, allowing the receptor-hormone complex to enter the nucleus (if it wasn't there already) and regulate gene activity Segment 3: Connection to the CourseThe hydrophilic ion channel lets ions cross the membrane without having to touch the hydrophobic core of the https://www.khanacademy.org/science/biology/membranes-and-transport/the-plasma-membrane/a/structure-of-the-plasma-membrane (phospholipid bilayer). Changes in ion levels inside the cell can change the activity of other molecules, such as ion-binding enzymes. The binding of neurotransmitters to neurons is also essential for the entire nervous system and basic brain functions such as attention, learning, and memory.  Intracellular receptors are unique because they cause these changes very directly, binding to the DNA and altering transcription themselves. A very important gas that acts as a ligand that is able to directly diffuse through the membrane is Nitric oxide (NO). It activates a signaling pathway in the smooth muscle surrounding blood vessels, one that makes the muscle relax and allows the blood vessels to expand. Drugs that treat heart diseases release NO to bind to the intracellular receptors and dilate vessels to restore blood flow to the heart. Thank you for listening to this episode of My AP Biology Thoughts. For more student-ran podcasts and digital content, make sure that you visit http://www.hvspn.com (www.hvspn.com). Thank you! Music Credits: "Ice Flow" Kevin MacLeod (incompetech.com) Licensed under Creative Commons: By Attribution 4.0 License http://creativecommons.org/licenses/by/4.0/ Subscribe to our Podcast https://podcasts.apple.com/us/podcast/my-ap-biology-thoughts/id1549942575 (Apple Podcasts) https://open.spotify.com/show/1nH8Ft9c9f6dmo75V9imCk (Spotify) https://podcasts.google.com/search/my%20ap%20biology%20thoughts (Google Podcasts )   https://www.youtube.com/channel/UC07e_nBHLyc_nyvjF6z-DVg (YouTube)   Connect with us on Social Media Twitterhttps://twitter.com/thehvspn ( @thehvspn)

Oxygen in, Carbon Dioxide out. We learn this basic paradigm about breathing from a very early age on. But how does it work? From a chemical viewpoint this is a lot of fun! So let's look into it

Sauerstoff rein, Kohlenstoffdioxid raus. Wir lernen dieses Grundprinzip unserer Atmung schon sehr früh, aber wie funktioniert das eigentlich? Vom Blickwinkel eines Chemikers macht dieses Thema einfach nur Spaß und deswegen, werden wir es uns ein bisschen näher anschauen

It's the six letter uncommon "L" words - nothing more lovely!  | LABARA  |  | LABRAL  |  | LAVABO  |  | LACTAM  |  | LACUNA  |  | LASCAR  | CRAALS/RASCAL,SCALAR,SACRAL | LAMPAD  |  | LANDAU  |  | LAAGER  |  | LANATE  |  | LAURAE  | LAURAS | LAOGAI  |  | LAGANS  | LAGAND | LAHALS  | HALALS, SLAHAL | LAHARS  |  | LAMIAS  |  | LANAIS  | LIANAS/NASIAL/SALINA | LATRIA  | LARIAT/ATRIAL | LALLAN  |  | LAMPAS  | PLASMA | LIBLAB  |  | LAMBED  | BLAMED/BEDLAM/BELDAM/AMBLED | LABILE  | LIABLE | JAYVEE  | VEEJAY | LIBRAE  |  | LAMBER  | AMBLER/BLAMER/MARBLE RAMBLE | LOBATE  | BOATEL/OBLATE | LABRET  |  | LABIUM  |  | LEACHY  |  | LEXICA  | ALEXIC  | LAUNCE  | LACUNE/UNLACE | LOCHIA  |  | LOCHAN  |  | LACILY  |  | LINACS  |  | LORICA  |  | LAZIED  |  | LALLED  |  | LADLER  |  | LAMMED  |  | LAMPED  | PALMED | LIGAND  | LADING | LADINO  |  | LADRON  | LARDON | LURDAN  |  | LATEEN  |  | LAVEER  | LEAVER/REVEAL/VEALER | LIGASE  | SILAGE | LAGUNE  | LANGUE | LEHUAS  |  | LAKIER  |  | LIENAL  | LINEAL | LAWINE  | LAUWINE | LARKER  |  | LEKVAR  |  | LANELY  | LEANLY | LEALLY  |  | LEALTY  | LATELY | LEMMAS  |  | LEMANS  | MENSAL | LANNER  |  | LEVANT  |  | LAPPET  | APPLET | LYSATE  |  | LYTTAE  |  | LOGGIA  |  | LAMING  | LINGAM/MALIGN | LAVING  |  | LAWING  | WALING |   |  | LONGAN  | LUNGAN | LANUGO  |  | LANGUR  |  | LOGWAY  |  | LITHIA  |  | LINHAY  | HYALIN | LIMINA  |  | LIKUTA  |  | LIPOMA  |  | LATTIN  |  | LASSIS  | SISALS | LAXITY  |  | LUNULA  |  | LOUMAS  |  | LARUMS  | MURALS | LORANS  |  | LARRUP  |  | LAPSUS  |  | LYSSAS  |  | LUBBER  |  | LEBENS  |  | LIBERS  | BIRLES | LIMBUS  |  | LOWBOY  |  | LOCOED  | COOLED | LECHWE  |  | LYCHES  | CHYLES | LUCKIE  |  | LECTIN  | LENTIC/CLIENT | LOCIES  | COLIES | LUCITE  | LUETIC | LOCULE  | LOCULI | LUCERN  |  | LITCHI  | LITHIC | LIMNIC  |  | LICTOR  |  | LOCUMS  |  | LOIDED  |  | LIEDER  | RELIED | LEKKED  |  | LEUDES  | ELUDES | LILIED  |  | LIMNED  | MILDEN | LODENS  |  | LOUPED  |  | LUPOID  | LUMPE

Talking about Reddit, Market Manipulation, Gamestop and more

Talking about Reddit, Market Manipulation, Gamestop and more

This is the second in a 3-Part Series of "The Weekly Bioanalysis" wherein the specialists at KCAS answer the question "What is Bioanalysis?" In this week's episode Dom and John discuss Large Molecules, Ligand Binding Assays (LBA) and Biomarkers."The Weekly Bioanalysis" is a podcast dedicated to discussing Bioanalytical news, tools and services related to the Pharmaceutical, Biopharmaceutical and Biomarker industries. Every week, KCAS will bring you another 30 minutes of friendly banter between our two finest Senior Scientific Advisors as they chat over coffee and brief themselves on what they've learned about the Bioanalytical world the past week.The Weekly Bioanalysis is brought to you by KCAS. KCAS is a progressive growing contract research organization of well over 100 talented and dedicated individuals committed to serving our clients and improving health worldwide. Our experienced scientists provide stand-alone bioanalytical services to the Pharmaceutical, Biopharmaceutical, Animal Health and Medical Device industries.

This is the third in our 3-Part Series of "The Weekly Bioanalysis" wherein the specialists at KCAS answer the question "What is Bioanalysis?" This week, Dom and John host their first-ever guests to the podcast to discuss Hybrid LC-MS/MS vs Ligand Binding Assays."The Weekly Bioanalysis" is a podcast dedicated to discussing Bioanalytical news, tools and services related to the Pharmaceutical, Biopharmaceutical and Biomarker industries. Every week, KCAS will bring you another 30 minutes of friendly banter between our two finest Senior Scientific Advisors as they chat over coffee and brief themselves on what they've learned about the Bioanalytical world the past week.The Weekly Bioanalysis is brought to you by KCAS. KCAS is a progressive growing contract research organization of well over 100 talented and dedicated individuals committed to serving our clients and improving health worldwide. Our experienced scientists provide stand-alone bioanalytical services to the Pharmaceutical, Biopharmaceutical, Animal Health and Medical Device industries.

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.18.389213v1?rss=1 Authors: Srinivas, R., Verma, N., Larson, E. C., Kraka, E. Abstract: In their previous work , Srinivas et al have shown that implicit fingerprints capture ligands and proteins in a shared latent space, typically for the purposes of virtual screening with collaborative filtering models applied on known bioactivity data. In this work, we extend these implicit fingerprints/descriptors using deep learning techniques to translate latent descriptors into discrete representations of molecules (SMILES), without explicitly optimizing for chemical properties . This allows the design of new compounds based upon the latent representation of nearby proteins, thereby encoding drug-like properties including binding affinities to known proteins. The implicit descriptor method does not require any fingerprint similarity search, which makes the method free of any bias arising from the empirical nature of the fingerprint models cite{srinivas2018implicit}. We evaluate the properties of the novel drugs generated by our approach using physical properties of drug-like molecules and chemical complexity. Additionally, we analyze the reliability of the biological activity of the new compounds generated using this method by employing models of protein ligand interaction, which assists in assessing the potential binding affinity of the designed compounds. We find that the generated compounds exhibit properties of chemically feasible compounds and are likely to be excellent binders to known proteins. Furthermore, we also analyze the diversity of compounds created using the Tanimoto distance and conclude that there is a wide diversity in the generated compounds. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.18.389155v1?rss=1 Authors: Guo, S., Vance, T., Zahiri, H., Eves, R., Stevens, C., Hehemann, J.-H., Vidal-Melgosa, S., Davies, P. Abstract: Carbohydrate recognition by lectins governs critical host-microbe interactions. MpPA14 lectin is a domain of a 1.5-MDa adhesin responsible for a symbiotic bacterium-diatom interaction in Antarctica. Here we show MpPA14 binds various monosaccharides, with L-fucose and N-acetyl glucosamine being the strongest ligands (Kd ~ 150 uM). High-resolution structures of MpPA14 with 15 different sugars bound elucidated the molecular basis for the lectin's apparent binding promiscuity but underlying selectivity. MpPA14 mediates strong Ca2+-dependent interactions with the 3, 4 diols of L-fucopyranose and glucopyranoses, and binds other sugars via their specific minor isomers. Thus, MpPA14 only binds polysaccharides like branched glucans and fucoidans with these free end-groups. Consistent with our findings, adhesion of MpPA14 to diatom cells was selectively blocked by L-fucose, but not by N-acetyl galactosamine. With MpPA14 lectin homologs present in adhesins of several pathogens, our work gives insight into an anti-adhesion strategy to block infection via ligand-based antagonists. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.13.381293v1?rss=1 Authors: Nguyen, G. T. T., Sutinen, A., Raasakka, A., Muruganandam, G., Loris, R., Kursula, P. Abstract: Charcot-Marie-Tooth disease (CMT) is one of the most common inherited neurological disorders. Despite the common involvement of ganglioside-induced differentiation-associated protein 1 (GDAP1) in CMT, the protein structure and function, as well as the pathogenic mechanisms, remain unclear. We determined the crystal structure of the complete human GDAP1 core domain, which shows a novel mode of dimerization within the glutathione S-transferase (GST) family. The long GDAP1-specific insertion forms an extended helix and a flexible loop. GDAP1 is catalytically inactive towards classical GST substrates. Through metabolite screening, we identified a ligand for GDAP1, the fatty acid hexadecanedioic acid, which is relevant for mitochondrial membrane permeability and Ca2+ homeostasis. The fatty acid binds to a pocket next to a CMT-linked residue cluster, increases protein stability, and induces changes in protein conformation and oligomerization. The closest homologue of GDAP1, GDAP1L1, is monomeric in its full-length form. Our results highlight the uniqueness of GDAP1 within the GST family and point towards allosteric mechanisms in regulating GDAP1 oligomeric state and function. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.09.373951v1?rss=1 Authors: Petroff, A., Weir, R. L., Yates, C. R., Ng, J. D., Baudry, J. Abstract: Stearoyl-CoA desaturase-1 (SCD1 or delta-9 desaturase, D9D) is a key metabolic protein that modulates cellular inflammation and stress, but overactivity of SCD1 is associated with diseases including cancer and metabolic syndrome. This transmembrane endoplasmic reticulum protein converts saturated fatty acids into monounsaturated fatty acids, primarily stearoyl-CoA into oleoyl-CoA, which are critical products for energy metabolism and membrane composition. The present computational molecular dynamics study characterizes the molecular dynamics of SCD1 with substrate, product, and as apoprotein. The modeling of SCD1:fatty acid interactions suggests that 1) SCD1:CoA moiety interactions open the substrate binding tunnel, 2) SCD1 stabilizes a substrate conformation favorable for desaturation, and 3) SCD1:product interactions result in an opening of the tunnel, possibly allowing product exit into the surrounding membrane. Together, these results describe a highly dynamic series of SCD1 conformations resulting from the enzyme:cofactor:substrate interplay that inform drug-discovery efforts. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.04.368233v1?rss=1 Authors: Tiwari, V., Borchardt, J. S., Schuh, A., Klug, C. S., Czajkowski, C. Abstract: Signaling in the brain depends on rapid opening and closing of pentameric ligand-gated ion channels (pLGICs). These proteins are the targets of various clinical drugs and, defects in their function is linked to a variety of diseases including myasthenia, epilepsy and sleep-disorders. While recent high-resolution structures of prokaryotic and eukaryotic pLGICs have shed light on the molecular architecture of these proteins, describing their conformational dynamics in physiological lipids is essential for understanding their function. Here, we used site-directed spin labeling electron paramagnetic resonance (SDSL EPR) spectroscopy and functional channels reconstituted in liposomes to reveal ligand-induced structural changes in the extracellular domain (ECD) of GLIC. Proton-activation caused an inward motion of labeled sites at the top of {beta}-strands ({beta}1, 2, 5, 6, 8) towards the channel lumen, consistent with an agonist-induced inward tilting motion of the ECD. Similar proton-dependent GLIC ECD motions were detected in the presence of a non-activating (gating deficient) mutation, suggesting that the inward tilting of the ECD does not accompany channel opening but is associated with an agonist-induced closed pre-activated channel state. These findings provide new insights into the protein dynamics underlying pLGIC gating transitions. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.03.367540v1?rss=1 Authors: Bali, N., Lee, H.-K., Zinn, K. Abstract: Control of tyrosine phosphorylation is an essential element of many cellular processes, including proliferation, differentiation neurite outgrowth, and synaptogenesis. Receptor-like protein-tyrosine phosphatases (RPTPs) have cytoplasmic phosphatase domains and cell adhesion molecule (CAM)-like extracellular domains that interact with cell-surface ligands and/or co-receptors. We identified a new ligand for the Drosophila Lar RPTP, the immunoglobulin superfamily CAM Sticks and Stones (Sns). Lar is orthologous to the three Type IIa mammalian RPTPs, PTPRF (LAR), PTPRD (PTP{delta}), and PTPRS (PTP{sigma}). Lar and Sns bind to each other in embryos and in vitro. The human Sns ortholog, Nephrin, binds to PTPRD and PTPRF. Genetic interaction studies show that Sns is essential to Lar's functions in several developmental contexts in the larval and adult nervous systems. In the larval neuromuscular system, Lar and sns transheterozygotes (Lar/sns transhets) have synaptic defects like those seen in Lar mutants and Sns knockdown animals. Lar and Sns reporters are both expressed in motor neurons and not in muscles, so Lar and Sns likely act in cis (in the same neurons). Lar mutants and Lar/sns transhets have identical axon guidance defects in the larval mushroom body in which Kenyon cell axons fail to stop at the midline and do not branch. Pupal Kenyon cell axon guidance is similarly affected, resulting in adult mushroom body defects. Lar is expressed in larval and pupal Kenyon cells, but Sns is not, so Lar-Sns interactions in this system must be in trans (between neurons). Lastly, R7 photoreceptor axons in Lar mutants and Lar/sns transhets fail to innervate the correct M6 layer of the medulla in the optic lobe. Lar acts cell-autonomously in R7s, while Sns is only in lamina and medulla neurons that arborize near the R7 target layer. Therefore, the Lar-Sns interactions that control R7 targeting also occur in trans. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.05.369645v1?rss=1 Authors: Aldehaiman, A., Momin, A. A., Restouin, A., Wang, L., Shi, X., Aljedani, S., Opi, S., Lugari, A., Hameed, U. F. S., Ponchon, L., Morelli, X., Huang, M., Dumas, C., Collette, Y., Arold, S. T. Abstract: The Nef protein of human and simian immunodeficiency viruses (HIV and SIV, respectively) boosts viral pathogenicity through its interactions with host cell proteins. Nef has a folded core domain and large flexible regions, each carrying several protein interaction sites. By combining the polyvalency intrinsic to unstructured regions with the binding selectivity and strength of a 3D folded domain, Nef can bind to many different host cell proteins, perturbing their cellular functions. For example, the combination of a linear proline-rich motif and a hydrophobic core domain surface allows Nef to increase affinity and selectivity for particular Src family SH3 domains. Here we investigated whether the interplay between Nefs flexible regions and its core domain can allosterically influence ligand selection. We found that the flexible regions can bind back to the core domain in different ways, producing distinct conformational states that alter the SH3 domain selectivity and availability of Nefs functional motifs. The resulting cross-talk might help synergising certain subsets of ligands while excluding others, promoting functionally coherent Nef-bound protein ensembles. Further, we combined proteomic and bioinformatic analyses to identify human proteins that select SH3 domains in the same way as does Nef. We found that only 2-3% of clones from a whole human fetal library displayed a Nef-like SH3 selectivity. However, in most cases this selectivity appears to be achieved by a canonical linear interaction rather than a Nef-like tertiary interaction. This analysis suggests that Nefs SH3 recognition surface has no (or marginally few) cellular counterparts, validating the Nef tertiary binding surface as a promising unique drug target. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.02.360958v1?rss=1 Authors: Sirois, I., Caron, E., Kovalchik, K. A., Wessling, L., Saab, F., Ma, Q., Despault, J., Kubiniok, P., Hamelin, D., Faridi, P., Li, C., Purcell, A. W., Tognetti, M., Reiter, L., Bruderer, R., Lanoix, J., Bonneil, E., Courcelles, M., Thibault, P. Abstract: Immunopeptidomics refers to the science of investigating the composition and dynamics of peptides presented by major histocompatibility complex (MHC) class I and class II molecules using mass spectrometry (MS). Here, we aim to provide a technical report to any non-expert in the field wishing to establish and/or optimize an immunopeptidomic workflow with relatively limited computational knowledge and resources. To this end, we thoroughly describe step-by-step instructions to isolate MHC class I and II-associated peptides from various biological sources, including mouse and human biospecimens. Most notably, we created MhcVizPipe (MVP) (https://github.com/CaronLab/MhcVizPipe), a new and easy-to-use open-source software tool to rapidly assess the quality and the specific enrichment of immunopeptidomic datasets upon the establishment of new workflows. In fact, MVP enables intuitive visualization of multiple immunopeptidomic datasets upon testing sample preparation protocols and new antibodies for the isolation of MHC class I and II peptides. In addition, MVP enables the identification of unexpected binding motifs and facilitates the analysis of non-canonical MHC peptides. We anticipate that the experimental and bioinformatic resources provided herein will represent a great starting point for any non-expert and will therefore foster the accessibility and expansion of the field to ultimately boost its maturity and impact. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.31.363309v1?rss=1 Authors: Weng, Y. L., Naik, S. R., Dingelstad, N., Kalyaanamoorthy, S., Ganesan, A. Abstract: The 2019 novel coronavirus pandemic caused by SARS-CoV-2 remains a serious health threat to humans and a number of countries are already in the middle of the second wave of infection. There is an urgent need to develop therapeutics against this deadly virus. Recent scientific evidences have suggested that the main protease (Mpro) enzyme in SARS-CoV-2 can be an ideal drug target due to its crucial role in the viral replication and transcription processes. Therefore, there are ongoing research efforts to identify drug candidates against SARS-CoV-2 Mpro that resulted in hundreds of X-ray crystal structures of ligand bound Mpro complexes in the protein data bank (PDB) that describe structural details of different chemotypes of fragments binding within different sites in Mpro. In this work, we perform rigorous molecular dynamics (MD) simulation of 62 reversible ligand-Mpro complexes in the PDB to gain mechanistic insights about their interactions at atomic level. Using a total of ~2.25 microseconds long MD trajectories, we identified and characterized different pockets and their conformational dynamics in the apo Mpro structure. Later, using the published PDB structures, we analyzed the dynamic interactions and binding affinity of small ligands within those pockets. Our results identified the key residues that stabilize the ligands in the catalytic sites and other pockets in Mpro. Our analyses unraveled the role of a lateral pocket in the catalytic site in Mpro that is critical for enhancing the ligand binding to the enzyme. We also highlighted the important contribution from HIS163 in this lateral pocket towards ligand binding and affinity against Mpro through computational mutation analyses. Further, we revealed the effects of explicit water molecules and Mpro dimerization in the ligand association with the target. Thus, comprehensive molecular level insights gained from this work can be useful to identify or design potent small molecule inhibitors against SARS-CoV-2 Mpro. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.30.362749v1?rss=1 Authors: Bhattarai, A., Pawnikar, S., Miao, Y. Abstract: Angiotensin converting enzyme 2 (ACE2) plays a key role in renin-angiotensin system regulation and amino acid homeostasis. Human ACE2 acts as the receptor for severe acute respiratory syndrome coronaviruses SARS-CoV and SARS-CoV-2. ACE2 is also widely expressed in epithelial cells of lungs, heart, kidney and pancreas. It is considered an important drug target for treating SARS-CoV-2, as well as pulmonary diseases, heart failure, hypertension, renal diseases and diabetes. Despite the critical importance, the mechanism of ligand binding to the human ACE2 receptor remains unknown. Here, we address this challenge through all-atom simulations using a novel ligand Gaussian accelerated molecular dynamics (LiGaMD) method. Microsecond LiGaMD simulations have successfully captured both binding and unbinding of the MLN-4760 inhibitor in the ACE2 receptor. In the ligand unbound state, the ACE2 receptor samples distinct Open, Partially Open and Closed conformations. Ligand binding biases the receptor conformational ensemble towards the Closed state. The LiGaMD simulations thus suggest a conformational selection mechanism for ligand recognition by the ACE2 receptor. Our simulation findings are expected to facilitate rational drug design of ACE2 against coronaviruses and other related human diseases. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.29.354696v1?rss=1 Authors: Obokata, N., Seki, C., Hirata, T., Maeda, J., Ishii, H., Nagai, Y., Matsumura, T., Takakuwa, M., Fukuda, H., Minamimoto, T., Kawamura, K., Zhang, M.-R., Nakajima, T., Saijo, T., Higuchi, M. Abstract: Purpose: Phosphodiesterase (PDE) 7 is a potential therapeutic target for neurological and inflammatory diseases, while in-vivo visualization of PDE7 has not been successful. In this study, we aimed to develop [11C]MTP38 as a novel positron emission tomography (PET) ligand for PDE7. Methods: [11C]MTP38 was radiosynthesized by 11C-cyanation of a bromo precursor with [11C]HCN. PET scans of rat and rhesus monkey brains and in-vitro autoradiography of brain sections derived from these species were conducted with [11C]MTP38. In monkeys, dynamic PET data were analyzed with an arterial input function to calculate the total distribution volume (VT). The non-displaceable binding potential (BPND) in the striatum was also determined by a reference tissue model with the cerebellar reference. Finally, striatal occupancy of PDE7 by an inhibitor was calculated in monkeys according to changes in BPND. Results: [11C]MTP38 was synthesized with radiochemical purity [≥] 99.4% and molar activity of 38.6 {+/-} 12.6 GBq/mol. Autoradiography revealed high radioactivity in the striatum and its reduction by non-radiolabeled ligands, in contrast with unaltered autoradiographic signals in other regions. In-vivo PET after radioligand injection to rats and monkeys demonstrated that radioactivity was rapidly distributed to the brain and intensely accumulated in the striatum relative to the cerebellum. Correspondingly, VT values estimated in the monkey striatum and cerebellum were 3.59 and 2.69 mL/cm3, respectively. The cerebellar VT value was unchanged by pretreatment with unlabeled MTP38. Striatal BPND was reduced in a dose-dependent manner after pretreatment with MTP-X, a PDE7 inhibitor. Relationships between the PDE7 occupancy by MTP-X and plasma MTP-X concentration could be described by Hill's sigmoidal function. Conclusion: We have provided the first successful preclinical demonstration of in-vivo PDE7 imaging with a specific PET radioligand. [11C]MTP38 is a feasible radioligand to evaluate PDE7 in the brain and is currently applied to a first-in-human PET study. Copy rights belong to original authors. Visit the link for more info

Dr. Vivian Chan is the founder and CEO of Sparrho, a platform that democratizes science using augmented intelligence. Dr. Chan has a PhD in biochemistry, and degrees in biotech. She has addressed the EU Ministers of Research and Innovation and keynoted the "Next Unicorn" series at Mobile World Congress.Episode NotesMusic used in the podcast: Higher Up, Silverman Sound StudioWere there fines in UK for leaving lock down in early COVID? Are there now? Under current regulations, organisers and facilitators of large gatherings (more than six) can be fined up to £10,000.Brits who do not wear a face covering in places where it is mandatory, such as in shops, supermarkets and on public transport, could be issued with a fine. Police can also break up any gatherings larger than six and can issue a £200 fine if they do not comply. Sparrho - www.sparrho.comB to B to C - It's the very definition of the oft-cited CPG industry “b-to-b-to-c” (b2b2c) model, where the supplier sells its products to retailers, who in turn sell to consumers. ... Many CPGs are today claiming a new focus on consumer centricity; that it's their consumer who matters, who they care about, and who they serve. (www.briansolis.com) B to B - Business-to-business, is a process for selling products or services to other businesses. Biotechnology - a broad area of biology, involving the use of living systems and organisms to develop or make products. (wikipedia)Biochemistry - the branch of science concerned with the chemical and physicochemical processes and substances that occur within living organisms. (wikipedia)Maths C covers additional pure-maths topics (including complex numbers, matrices, vectors, further calculus and number theory). Maths C gives the students an understanding of the methods and principles of mathematics and the ability to apply them in everyday situations and in purely mathematical contexts; the capacity to model actual situations and deduce properties from the model. (wikipedia)Structural Biology - a branch of molecular biology, biochemistry, and biophysics concerned with the molecular structure of biological macromolecules (especially proteins, made up of amino acids, RNA or DNA, made up of nucleotides, membranes, made up of lipids) how they acquire the structures they have, and how alterations in their structures affect their function. (wikipedia)RNA - ribonucleic acid, a nucleic acid present in all living cells. Its principal role is to act as a messenger carrying instructions from DNA for controlling the synthesis of proteins, although in some viruses RNA rather than DNA carries the genetic information. X-ray crystallography - the study of crystals and their structure by means of X-ray diffraction.Homeostasis - the tendency toward a relatively stable equilibrium between interdependent elements, especially as maintained by physiological processes.Ligand - is an ion or molecule (functional group) that binds to a central metal atom to form a coordination complex. The bonding with the metal generally involves formal donation of one or more of the ligand's electron pairs.

Wir setzen die Pharmakolgie-Reihe mit einer weiteren Folge um einen der wesentlichen Grundbegriffe fort. In dieser Folge versuchen wir uns der Pharmakodynamik zu nähern. - Wie? (Reversibel oder irreversibel) - Wo? (Körpereigene Proteine (Rezeptoren, Enzyme, Kohlenhydrate, Fette, RNA/DNA) oder körperfremde (Viren, Bakterien) - Was? (Agonismus/Antagonismus, andere Form der Modulation) Pharmakodynamik beschreibt die Prozesse, die ein Medikament im Organsimus in Gang setzt. Der wichtigste Punkt ist hier die Interaktion mit Rezeptoren. Anni, Clemens und Ingmar versuchen einen roten Faden in einem Thema zu halten, das einem zwar vertraut vorkommt, bei näherem hinsehen aber durchaus seine Tücken aufweist. Wir freuen uns, das Ralf trotz anfänglicher technischer Anlaufschwierigkeiten es noch geschafft hat die Runde zu komplettieren. Fortbildungspunkte werden auf der Homepage des Podcast innerhalb von 4 Wochen nach Veröffentlichung erfasst.

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.27.315762v1?rss=1 Authors: Yang, L., He, W., Yun, Y., Gao, Y., Zhu, Z., Teng, M., Liang, Z., Niu, L. Abstract: Uncovering conserved 3D protein-ligand binding patterns at the basis of functional groups (FGs) shared by a variety of small molecules can greatly expand our knowledge of protein-ligand interactions. Despite that conserved binding patterns for a few commonly used FGs have been reported in the literature, large-scale identification and evaluation of FG-based 3D binding motifs are still lacking. Here, we developed AFTME, an alignment-free method for automatic mapping of 3D motifs to different FGs of a specific ligand through two-dimensional clustering. Applying our method to 233 nature-existing ligands, we defined 481 FG-binding motifs that are highly conserved across different ligand-binding pockets. Systematic analysis further reveals four main classes of binding motifs corresponding to distinct sets of FGs. Combinations of FG-binding motifs facilitate proteins to bind a wide spectrum of ligands with various binding affinities. Finally, we showed that these general binding patterns are also applicable to target-drug interactions, providing new insights into structure-based drug design. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.28.316224v1?rss=1 Authors: Ahmed, A., Mam, B., Sowdhamini, R. Abstract: Protein-ligand binding prediction has extensive biological significance. Binding affinity helps in understanding the degree of protein-ligand interactions and has wide protein applications. Protein-ligand docking using virtual screening and molecular dynamic simulations are required to predict the binding affinity of a ligand to its cognate receptor. In order to perform such analyses, it requires intense computational power and it becomes impossible to cover the entire chemical space of small molecules. It has been aided by a shift towards using Machine Learning-based methodologies that aids in binding prediction using regression. Recent developments using deep learning has enabled us to make sense of massive amounts of complex datasets. Herein, the ability of the model to learn intrinsic patterns in a complex plane of data is the strength of the approach. Here, we have incorporated Convolutional Neural Networks that find spatial relationships among data to help us predict affinity of binding of proteins in whole superfamilies towards a diverse set of ligands. The models were trained and validated using a detailed methodology for feature extraction. We have also tested DEELIG on protein complexes relevant to the current public health scenario. Our approach to network construction and training on protein-ligand dataset prepared in-house has provided significantly better results than previously existing methods in the field. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.27.315796v1?rss=1 Authors: Bauer, M. S., Gruber, S., Milles, L. F., Nicolaus, T., Schendel, L. C., Gaub, H. E., Lipfert, J. Abstract: The current COVID-19 pandemic has a devastating global impact and is caused by the SARS-CoV-2 virus. SARS-CoV-2 attaches to human host cells through interaction of its receptor binding domain (RBD) located on the viral Spike (S) glycoprotein with angiotensin converting enzyme-2 (ACE2) on the surface of host cells. RBD binding to ACE2 is a critical first step in SARS-CoV-2 infection. Viral attachment occurs in dynamic environments where forces act on the binding partners and multivalent interactions play central roles, creating an urgent need for assays that can quantitate SARS-CoV-2 interactions with ACE2 under mechanical load and in defined geometries. Here, we introduce a tethered ligand assay that comprises the RBD and the ACE2 ectodomain joined by a flexible peptide linker. Using specific molecular handles, we tether the fusion proteins between a functionalized flow cell surface and magnetic beads in magnetic tweezers. We observe repeated interactions of RBD and ACE2 under constant loads and can fully quantify the force dependence and kinetics of the binding interaction. Our results suggest that the SARS-CoV-2 ACE2 interaction has higher mechanical stability, a larger free energy of binding, and a lower off-rate than that of SARS-CoV-1, the causative agents of the 2002-2004 SARS outbreak. In the absence of force, the SARS-CoV-2 RBD rapidly (within [≤]1 ms) engages the ACE2 receptor if held in close proximity and remains bound to ACE2 for 400-800 s, much longer than what has been reported for other viruses engaging their cellular receptors. We anticipate that our assay will be a powerful tool investigate the roles of mutations in the RBD that might alter the infectivity of the virus and to test the modes of action of neutralizing antibodies and other agents designed to block RBD binding to ACE2 that are currently developed as potential COVID-19 therapeutics. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.09.22.298109v1?rss=1 Authors: Shang, J., Kojetin, D. Abstract: Ligands bind to an occluded orthosteric pocket within the nuclear receptor (NR) ligand-binding domain (LBD), but experimentally it remains unclear whether ligand binding proceeds through induced fit or conformational selection mechanisms. Using NMR spectroscopy lineshape analysis, we show that ligand binding to the peroxisome proliferator-activated receptor gamma (PPAR{gamma}) LBD involves a two-step induced fit mechanism including an initial fast step followed by slow conformational change. Surface plasmon resonance and isothermal titration calorimetry heat capacity analysis support the fast kinetic binding step and the conformational change after binding step. The putative initial ligand binding pose is suggested in several crystal structures of PPAR{gamma} LBD where a ligand is bound to a surface pore formed by helix 3, the {beta}-sheet, and the {Omega} loop; one of several ligand entry sites suggested in previous targeted and unbiased molecular simulations. These findings, when considered with a recent NMR study showing the activation function-2 (AF-2) helix 12 exchanges in and out of the orthosteric pocket in apo/ligand-free PPAR{gamma}, suggest an activation mechanism whereby agonist binding occurs through an initial encounter complex with the LBD followed by transition of the ligand into the orthosteric pocket concomitant with a conformational change resulting in a solvent-exposed active helix 12 conformation. Copy rights belong to original authors. Visit the link for more info

Styrketrening: Fra Bro til pro - 
Del 6 med Moritz Michaelis Tor Andre Sandum.  PERIODISERING og PROGRESJON
Vi snakker løst og fast om hvordan du bør periodisere treningen din for å få progresjon. 
Hva er lineær progresjon?
Hvilken periodiseringsmodell er best? 
Hva er det viktigste du bør gjøre for å sikre deg fremgang?
Og Hva har dette med en okse å gjøre?  Bakgrunn:
Vi bestemte oss for å ta for oss tema styrketrening. Gjennom flere episoder kommer vil til å gå gjennom hva styrketrening er, hvordan du bør trene, hva som skjer når du bygger muskler og blir sterkere, vanlige feil og massa,masse mer.  Målet vårt med disse episodene er å få deg som lytter til å få en bedre forståelse for hva muskler faktisk er og hva vi må gjøre for å blir større og sterkere. 
Dette vil ikke bare gjøre at du får ett bedre innblikk i hvordan og hva du bør trene, men det vil også hjelpe deg til være kritisk til ting på 
SoMe eller generelt på internet. Rett og slett STYRKETRENING: Fra bro til pro
Har du ris og ros eller noe spørsmål/ønsker angående episodene så send oss en melding! Sandum på instagram:
https://instagram.com/sandumpt?igshid=1h666b5u63sqe Nyhetsbrevet hand kan du abonnere på her:
https://sandumpt.no/artikler/ 
Jeff Nippard sin YouTube serie om fullkroppstrening finner du her:  https://www.youtube.com/playlist?list=PLp4G6oBUcv8zeDXbOiCu4AKcs9nlRSjYY https://youtu.be/eTxO5ZMxcsc Her er artikkelen Sandum snakket om: 
https://github.com/linkel/Ligand/blob/master/content/Norwegian_High_Frequency_Programs.md
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Har du spørsmål eller ønsker du å komme i kontakt med meg for hjelp med kosthold, livsstil og trening, eller har du interesse i online oppfølging?
Du finner du alt du trenger å vite her: https://www.ptservice.no/online-coaching/ _
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Eller send en mail til:
Moritz@ptservice.no 
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Følg meg gjerne på Instagram for memes, mat, treningsbilder, fakta og repost av studier :  https://www.instagram.com/mini_morimi/